ArticlePloS one2015
Genome wide analysis of flowering time trait in multiple environments via high-throughput genotyping technique in Brassica napus L.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 35 citations in OpenAlex.
- Multifactor Analysis of a Genome-Wide Selection System inPlants (Basel, Switzerland) · 2025Article
- Integrating GWAS, RNA-Seq and functional analysis revealed that BnaA02.SE mediates silique elongation by affecting cell proliferation and expansion in Brassica napus.Plant biotechnology journal · 2024Article
- Discovering novel genomic regions explaining adaptation of bread wheat to conservation agriculture through GWAS.Scientific reports · 2024Article
- CRISPR/Cas9-Mediated Targeted Mutagenesis ofInternational journal of molecular sciences · 2022Article
- Sparse bayesian learning for genomic selection in yeast.Frontiers in bioinformatics · 2022Article
- Exploring the gene pool of Brassica napus by genomics-based approaches.Plant biotechnology journal · 2021Review
- Knock-out of TERMINAL FLOWER 1 genes altered flowering time and plant architecture in Brassica napus.BMC genetics · 2020Article
- Joint QTL mapping and transcriptome sequencing analysis reveal candidate flowering time genes in Brassica napus L.BMC genomics · 2019Article
- Article
- QTL and Candidate Gene Identification for Silique Length Based on High-Dense Genetic Map inFrontiers in plant science · 2019Article
- Translating Flowering Time From Arabidopsis thaliana to Brassicaceae and Asteraceae Crop Species.Plants (Basel, Switzerland) · 2018Review
- Exploitation of data from breeding programs supports rapid implementation of genomic selection for key agronomic traits in perennial ryegrass.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2018Article
- Earliness traits in rapeseed (Brassica napus): SNP loci and candidate genes identified by genome-wide association analysis.DNA research : an international journal for rapid publication of reports on genes and genomes · 2018Article
- Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2018Article
- Quantile regression for genome-wide association study of flowering time-related traits in common bean.PloS one · 2018Article
- Major Co-localized QTL for Plant Height, Branch Initiation Height, Stem Diameter, and Flowering Time in an Alien Introgression DerivedFrontiers in plant science · 2018Article
- Breeding histories and selection criteria for oilseed rape in Europe and China identified by genome wide pedigree dissection.Scientific reports · 2017Article
- Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus.Scientific reports · 2017Article
- A Genome-Wide Association Study Reveals New Loci for Resistance to Clubroot Disease inFrontiers in plant science · 2016Article
- Seed Quality Traits Can Be Predicted with High Accuracy in Brassica napus Using Genomic Data.PloS one · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The prediction of the flowering time (FT) trait in Brassica napus based on genome-wide markers and the detection of underlying genetic factors is important not only for oilseed producers around the world but also for the other crop industry in the rotation system in China. In previous studies the low density and mixture of biomarkers used obstructed genomic selection in B. napus and comprehensive mapping of FT related loci. In this study, a high-density genome-wide SNP set was genotyped from a double-haploid population of B. napus. We first performed genomic prediction of FT traits in B. napus using SNPs across the genome under ten environments of three geographic regions via eight existing genomic predictive models. The results showed that all the models achieved comparably high accuracies, verifying the feasibility of genomic prediction in B. napus. Next, we performed a large-scale mapping of FT related loci among three regions, and found 437 associated SNPs, some of which represented known FT genes, such as AP1 and PHYE. The genes tagged by the associated SNPs were enriched in biological processes involved in the formation of flowers. Epistasis analysis showed that significant interactions were found between detected loci, even among some known FT related genes. All the results showed that our large scale and high-density genotype data are of great practical and scientific values for B. napus. To our best knowledge, this is the first evaluation of genomic selection models in B. napus based on a high-density SNP dataset and large-scale mapping of FT loci.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.